Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# YOUR CODE HERE
df_2007 = df[df["year"] == 2007][["continent", "pop"]]
df_cont = df_2007.groupby("continent").sum().sort_values("continent")
print(df_cont.head())
fig = px.bar(df_cont, x="pop", color=["blue", "red", "yellow", "purple", "orange"], text_auto='.2')
fig.show()
#category_orders={"contintent":["Africa", "Americas", "Asia", "Europe", "Oceania"]}
pop continent Africa 929539692 Americas 898871184 Asia 3811953827 Europe 586098529 Oceania 24549947
# YOUR CODE HERE
fig.update_yaxes(categoryorder="total ascending")
fig.show()
Add text to each bar that represents the population
# YOUR CODE HERE
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
# YOUR CODE HERE
df_sum = df[["continent", "year", "pop"]].groupby(["continent", "year"]).sum("pop").reset_index()
fig = px.bar(df_sum, x="pop", y="continent", color="continent",
animation_frame="year", range_x=[0,4000000000])
fig.update_yaxes(categoryorder="total ascending")
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
# YOUR CODE HERE
df_sum2 = df[["country", "year", "pop"]].groupby(["country", "year"]).sum("pop").reset_index()
fig = px.bar(df_sum2, x="pop", y="country", color="country", animation_frame="year", )
fig.update_yaxes(categoryorder="total ascending")
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
# YOUR CODE HERE
fig.update_layout(height=1000)
fig.show()
# YOUR CODE HERE
fig.update_yaxes(range=[131.5, 141.5])
fig.update_layout(height=500)
fig.show()